Parcels-code/Parcels - Open Source PR Review Scorecard

Main code for Parcels - a highly customisable Lagrangian simulation framework

C-Rank Grade: A (Welcoming) - 67/100

External PR Merge Rate: 82%

Response Time: -

First Timer Success: 88%

Frequently Asked Questions

Is Parcels-code/Parcels welcoming to first-time open-source contributors?

Parcels-code/Parcels has a recorded first-timer success rate of 87.5%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in Parcels-code/Parcels respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 67.4 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 67.4 places Parcels-code/Parcels in the A tier.

What is the external contributor pull request merge rate for Parcels-code/Parcels?

The external contributor pull request merge rate for Parcels-code/Parcels is 82.2%, based on public PR activity from non-core contributors.

Are there Good First Issues available in Parcels-code/Parcels?

Parcels-code/Parcels currently has 4 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

Parcels-code
Parcels-code/ParcelsA•Welcoming366
GitHub
Back to Explorer
Parcels-code

Parcels-code/Parcels

366
InactiveA•Welcoming(67/100)Python

Main code for Parcels - a highly customisable Lagrangian simulation framework

GitHub
Compare••
Jump to:

AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
8.6/10
Patience Score
8.6/10
Nitpick Rate
35%

Highly welcoming maintainers in Parcels-code/Parcels. Prompt code reviews with positive guidance for new contributors.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
82.2%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
87.5%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
12 core
Highly collaborative maintainer core
Diagnostic Health HUD
82.2%
Merge Gauge
87.5%
1st-Timer
Community Vibe59/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for Parcels-code/Parcels
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/Parcels-code/Parcels)](https://getmerged.abhishekco.de/Parcels-code/Parcels?utm_source=github&utm_medium=badge)

Active Good First Issues (5)

View on GitHub

Now that we have Parquet output, its really easy to integrate this into Kepler.gl for exploratory analysis. Its nice to use Matplotlib for visualisations in the notebooks, but I think it would be better to recommend users use Kepler for their EDA as its much more interactive, and scales up nicer. **Using the same data from https://docs.parcels-code.org/en/main/user_guide/getting_started/tutorial_output.html ** Kepler version: kepler.mp4 Matplotlib version: Screen.Recording.2026-08-31.at.14.42.51.mov

📅 Opened Aug 31, 2026💬 4 comments
Quality: 100/100Contribute

What version of Parcels are you running? main Is your feature request related to a problem? Currently notebooks and doc pages show cell inputs and outputs in their entirety. There are cases where we don't want this: Plotting code - we would want to use a hide-input cell tag to put the cell inputs in a collapsable block Code for cleaning up .parquet temporary files - we would want to use remove-input and remove-output cell tags to completely hide these cells This can be controlled via myst-nb cell tags, and gives us more control over what we draw attention to in our documentation. Describe the solution you'd like Applying of cell tags appropriately. Note generally that when working with myst formatting the web browser version of jupyter lab (i.e., via the jupyter lab local server) is better as it shows rich previews, compared to the vscode version of Jupyter which doesn't support myst. Describe alternatives you've considered No response Additional context No response

📅 Opened Jul 24, 2026💬 4 comments
Quality: 50/100Contribute

Hmm, this would also return True for a B-grid (where U and V are on the same node, but W and tracers are on different nodes). So the naming here is not correct. Perhaps change to _is_cgrid and then return the negate? Originally posted by @erikvansebille in #2646 (comment)

📅 Opened Jun 23, 2026💬 0 comments
Quality: 25/100Contribute

What version of Parcels are you running? v4 Is your feature request related to a problem? Running pytest tests/ now throws a lot of warnings (see list below for 481decc). Although a few of these are upstream (so we can't solve them), most of these are in our own code. It would be good to fix these Once the list is empty, we can implement #2413 to fail on warnings src/parcels/_datasets/remote.py:195 tests/test_advection.py::test_nemo_curvilinear_fieldset tests/test_convert.py::test_convert_nemo_offsets tests/test_index_search.py::test_indexing_nemo_curvilinear /Users/erik/Codes/parcels/src/parcels/_datasets/remote.py:195: FutureWarning: dropping variables using `drop` is deprecated; use drop_vars. return ds.isel(time=0).drop(["time"]) tests/sgrid/test_accessor.py: 214 warnings tests/test_advection.py: 12 warnings /Users/erik/Codes/parcels/src/parcels/_sgrid/accessor.py:101: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in f

📅 Opened Jun 17, 2026💬 0 comments
Quality: 90/100Contribute

What version of Parcels are you running? N/A Is your feature request related to a problem? Currently the ParticleSet.execute(...,verbose_progress=True) progress bar prints a new line to job logs if run from a non-interactive shell, e.g. from slurm. Describe the solution you'd like This could possibly be prevented by catching the type of shell and handling the progress bar accordingly. Describe alternatives you've considered No response Additional context No response

📅 Opened Jun 16, 2026💬 3 comments
Quality: 40/100Contribute
Looking for more Python beginner tasks?Explore Python GFI

Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for Parcels-code/Parcels

When evaluating whether to contribute to Parcels-code/Parcels, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of Parcels-code/Parcels acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 82.2% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to Parcels-code/Parcels

01

Is Parcels-code/Parcels welcoming to first-time open-source contributors?

Parcels-code/Parcels has a recorded first-timer success rate of 87.5%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 67.4 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 67.4 places Parcels-code/Parcels in the Welcoming tier.

04

What is the external contributor pull request merge rate for Parcels-code/Parcels?

The external pull request merge rate is 82.2%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in Parcels-code/Parcels?

Yes, Parcels-code/Parcels currently has 4 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for Parcels-code/Parcels are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.